The role of data in the strategic design field is unquestionable and essential, being a catalyst for creativity and decision making. Design teams gather large amounts of data at the beginning of projects, to understand how the context of the problem looks like and how they can get inspired for the ideation of the outcomes. In the context of this Master thesis, data is the first pillar of an input-output processing system, which is used in the field of strategic design (process) and can result in new business models (output). Until now, design practitioners have relied highly on manual data saving (whiteboards, post-its and notebooks). Digital data saving, on the other hand, can ensure that data and the embedded knowledge are not lost or damaged and that can be easily retrieved. Especially within bigger teams where there are multiple data and knowledge creators, it so happens that the knowledge gap between novice and expert designers is large. This typically results in the hindering of quality of the outcomes of design projects, as team members are limited to their own data and knowledge accessible to them, as opposed to the entirety of the team. The second pillar is the process, referred to as strategic design. Business Models Inc. (BMI), a design consultancy for strategy and innovation in Amsterdam, makes use of a variant of strategic design, which is known as Business Design. At BMI, data is used extensively in the understanding phase of the design project and ideation, where the goal is not only to get the Business Design team inspired but also the client, who co-creates with them. The type of data that they make use of is, therefore, a combination of quantitative (e.g. consumer surveys, market outlooks, financial statements of the client) and qualitative (e.g. their curated collection of business models, SWOT analysis, customer interviews and co-creation sessions). This type of data helps the team create new business models and value propositions, which are the output of the input-output processing system. There is an increasing trend in the design industry to start incorporating data science practices, allowing designers to have access to new insights which are up to date and can be shared among team members. This has been proposed in literature and applied already in the design industry, for instance, design consultancies already combining data science with design thinking tools. The premise of this project starts with wondering how the ideation of new business models and value propositions could be further enriched if a data science approach would continue to be welcomed in the design field. The outcome of this project has explored what the best utilization of data would be within the design process, hinting at an exploited usage of data in ideation. The final concept is a 3-horizon roadmap that exposes how BMI could firstly, organize their data; secondly, find it as efficiently as possible, and thirdly, inspire a new customer segment in the creation of new business models and value propositions.